Machine Learning Engineer, MLOps Enginner

Looking for an experienced MLOps Engineer to build and scale machine learning solutions that address critical challenges in the healthcare revenue cycle. Report to Experian Health and focus on operationalizing ML models, ensuring deployment pipelines, and maintaining scalable, secure, and ML infrastructure on AWS, collaborate with data scientists, software engineers, and product teams to bring ML products from prototype to production, with a emphasis on automation, monitoring, and continuous improvement. You'll have opportunity to:

Develop scalable MLOps pipelines for model training, validation, deployment, and monitoring using AWS services.

Implement infrastructure as code and CI/CD workflows to support rapid experimentation and reliable production releases.

Collaborate with data scientists to productionize ML models and ensure reproducibility, versioning, and traceability.

Monitor model performance and data drift in production environments, and implement automated retraining and alerting mechanisms.

Improve ML workflows using tools such as SageMaker, Airflow, Docker, Kubernetes (EKS), and Step Functions.

Ensure compliance with healthcare data standards and security best practices (e.g., HIPAA)